f93ca5174a1a31c362de0d5a5330f99c77a6ad42,keras/engine/training.py,Model,load_weights,#Model#Any#Any#Any#Any#,2158

Before Change

    if _is_hdf5_filepath(filepath):
      save_format = "h5"
    else:
      try:
        tf.compat.v1.train.NewCheckpointReader(filepath)
        save_format = "tf"
      except tf.errors.DataLossError:
        // The checkpoint is not readable in TensorFlow format. Try HDF5.
        save_format = "h5"
    if save_format == "tf":
      status = self._trackable_saver.restore(filepath, options)
      if by_name:
        raise NotImplementedError(

After Change

          "When calling model.load_weights, skip_mismatch can only be set to "
          "True when by_name is True.")

    filepath, save_format = _detect_save_format(filepath)
    if save_format == "tf":
      status = self._trackable_saver.restore(filepath, options)
      if by_name:

Instances